RRepoGEO

REPOGEO REPORT · LITE

chiphuyen/lazynlp

Default branch master · commit dbf794f5 · scanned 5/12/2026, 8:52:01 AM

GitHub: 2,257 stars · 322 forks

AI VISIBILITY SCORE
35 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface chiphuyen/lazynlp, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Reposition the README's opening statement to emphasize LLM dataset creation

    Why:

    CURRENT
    A straightforward library that allows you to crawl, clean up, and deduplicate webpages to create massive monolingual datasets. Using this library, you should be able to create datasets larger than the one used by OpenAI for GPT-2.
    COPY-PASTE FIX
    **lazynlp** is a Python library for efficiently scraping, cleaning, and deduplicating web pages to create massive, high-quality text datasets, ideal for training large language models (LLMs) and other AI applications. It enables building datasets larger than those used by models like GPT-2.
  • highlicense#2
    Add a LICENSE file to the repository root

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root with your chosen open-source license (e.g., MIT, Apache-2.0, GPL-3.0). This is crucial for clarity and adoption.
  • mediumhomepage#3
    Add a Homepage URL to the repository's 'About' section

    Why:

    COPY-PASTE FIX
    Add a URL to the 'Homepage' field in the repository's 'About' section. This could be a project website, documentation, or a relevant blog post.

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface chiphuyen/lazynlp
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
scrapy/scrapy
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. scrapy/scrapy · recommended 1×
  2. crummy/BeautifulSoup · recommended 1×
  3. psf/requests · recommended 1×
  4. apache/kafka · recommended 1×
  5. pandas-dev/pandas · recommended 1×
  • CATEGORY QUERY
    How to efficiently build massive text datasets by scraping and cleaning web content?
    you: not recommended
    AI recommended (in order):
    1. Scrapy (scrapy/scrapy)
    2. Beautiful Soup 4 (crummy/BeautifulSoup)
    3. Requests (psf/requests)
    4. Apache Kafka (apache/kafka)
    5. Pandas (pandas-dev/pandas)
    6. spaCy (explosion/spaCy)
    7. NLTK (nltk/nltk)
    8. MinIO (minio/minio)
    9. Amazon S3
    10. Google Cloud Storage

    AI recommended 10 alternatives but never named chiphuyen/lazynlp. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help prepare clean, deduplicated web data for training large language models?
    you: not recommended
    AI recommended (in order):
    1. Apache Spark
    2. Databricks
    3. Dedupe.io
    4. Apache Flink
    5. Pandas
    6. Scrapy
    7. Dataiku DSS

    AI recommended 7 alternatives but never named chiphuyen/lazynlp. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of chiphuyen/lazynlp?
    pass
    AI named chiphuyen/lazynlp explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts chiphuyen/lazynlp in production, what risks or prerequisites should they evaluate first?
    pass
    AI named chiphuyen/lazynlp explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo chiphuyen/lazynlp solve, and who is the primary audience?
    pass
    AI named chiphuyen/lazynlp explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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chiphuyen/lazynlp — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite